Using LDL particle number to guide statin therapy in high-risk patients

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 - cholesterol

Over the last few decades cardiologists and primary care physicians have increasingly relied on low-density lipoprotein cholesterol (LDL-C) as a central tenant of clinical practice to guide statin therapy for dyslipidemic patients. However, the large numbers of individuals experiencing cardiovascular events while on statin therapy would seem to suggest that LDL-C levels are an imperfect measure of LDL. Yet many clinicians continue to focus on LDL-C, whether out of habit, inertia or lack of time to understand alternative measures of LDL, such as LDL particle (LDL-P) number. A growing body of evidence suggests that their patients would be better served if clinicians used LDL-P as a management tool for high-risk patients.

Our team recently completed a study suggesting that use of a target LDL-P number to guide statin therapy in at-risk patients may reduce the risk of major adverse cardiovascular events (MACE) and death due to cardiovascular disease (CVD), compared to using the historical measure of LDL, LDL-C as a guide to statin therapy. The benefits of using LDL-P are particularly pronounced in patients in whom LDL-P and LDL-C numbers are discordant, as is common in individuals with diabetes mellitus or coronary heart disease (CHD). 

Discordance occurs when alternate measures of LDL, LDL-P and LDL-C disagree due to variability in the amount of cholesterol per particle. Our findings were derived through use of the Archimedes Model, a clinically detailed simulation model of human physiology, diseases, interventions and healthcare systems, validated in more than 50 clinical trials. The Archimedes Model incorporates person-specific data from real populations to create simulated populations that match individuals to demographic, risk factor and biomarker profiles over time. It thus provides insight into likely health outcomes and costs under various interventions and assumptions, allowing researchers to model populations over longer periods of time and with a greater number of patients than is possible in a clinical trial.

We used the Archimedes Model to evaluate the efficacy of using LDL-C- versus LDL-P-guided therapy to prevent CVD events in patients with dyslipidemia. The model accounted for inter-relationships of patients’ baseline characteristics and risk factors, underlying physiological parameters and statin therapy effects to estimate CVD morbidity and mortality.

The population simulated consisted of 1 million individuals representative of the general U.S. population aged 20- to 84, which were derived from the National Health and Nutrition Examination Survey 1999-2006. We also examined subpopulations of dyslipidemic individuals at moderate or high risk of CHD, patients with diagnosed diabetes, and those with prior CHD.

The simulated study had three arms:

  • Control: Virtual patients were evaluated for therapy for elevated LDL-C and treated with statins to standard LDL-C goals (less than 100 mg/dL for high-risk patients, less than 130 mg/dL for medium-risk patients,  less than 160 mg/dL for low-risk patients), in accordance with the NCEP Adult Treatment Panel III (ATP III) guidelines.
  • LDL-P alone: Patients were evaluated and treated based solely on their LDL-P values (target less than 1,053 nmol/L for high-risk patients, less than 1,383 nmol/L for medium-risk patients, less than 1,709 nmol/L for low-risk patients), as measured by nuclear magnetic resonance  spectroscopy.
  • Dual goals: Patients were evaluated for therapy using LDL-C alone, but treated to both LDL-C and LDL-P goals.

Our analysis suggests that managing at-risk patients to LDL-P goals resulted in fewer CVD events over the time frame of five, 10 and 20 years. The model showed that statin therapy in both the LDL-P alone arm and the dual arm reduced MACE (defined as fatal and nonfatal MI, fatal and nonfatal stroke, and CVD death) and death due to CVD (defined as CHD or stroke) to a greater extent than in the control arm.

However, we observed a slightly greater effect in the LDL-P arm than in the dual arm. In patients with established CHD, the relative reduction in risk of MACE relative to controls was 6.2 percent in the dual arm and 6.6 percent in the LDL-P alone arm. In patients with diabetes, the relative risk reduction versus the control arm was 7.3 percent in the LDL-P Alone arm and 6.9 percent in the dual arm.

The model also suggests that more widespread use of LDL-P would greatly increase statin use, though it would not do so indiscriminately. Rather, measuring LDL-P would help clinicians identify individuals with elevated LDL levels despite low or normal LDL-C, thereby enabling more efficient targeting of therapy to truly high-risk patients. While this would result in a net increase in statin use, patients with low LDL-P and high LDL-C would not be treated with statins if LDL-P alone were measured, thereby sparing patients (and the healthcare system) the cost and inconvenience of unnecessary treatment.

There is ample literature to support it the standard use of LDL-P to manage LDL related risk. I hope greater numbers of clinicians will agree with me that LDL-P is a much better marker for guiding statin therapy in at-risk patients.

Richard Kahn is the former chief scientific and medical officer of the American Diabetes Association and a professor of medicine at the University of North Carolina at Chapel Hill.